The case for normative economics

The epithet dismal science is often used to dismiss economics and its practitioners. This is unfair in many respects. Those who think economics is dismal are advised to have a look at Kilkenomics, the world’s first economics and comedy festival which celebrated its tenth anniversary in 2019. As for whether it’s a science, the jury is still out.

If we define science as what Ernest Nagel called the search for “repeatable patterns of dependence”, (here, p4) then economics could indeed be classed as a science. But if we define it as a reliance on experimental method, Robert Heilbroner suggests that this “throws into limbo certain central ideas of economics, such as value or utility, for which no experiments seem to be possible”.  Since Heilbroner wrote these words almost 50 years ago, there has been a considerable amount of progress in experimentally testing some of these central economic hypotheses, thanks to the work of people like Daniel Kahneman, who has applied psychological techniques to key economic concepts. But still the debate rages.

The moral dimension

I raise this question because it throws up an important issue: that of value judgement in economics. A discipline which pursues the cold hard logic of the physical sciences has no room to make moral judgements. But one of the pioneers in the field of economics was Adam Smith, who in 1759 wrote a book titled The Theory of Moral Sentiments. As titles go, that is as far away from value free economics as you can imagine. More importantly, it provided the ethical, philosophical, psychological, and methodological underpinnings for Smith's later work such as The Wealth of Nations which is now regarded as the first great work in western economics.

Over time, economics moved away from its philosophical roots and by the 1930s, neoclassical economists argued that since the notions of utility and culture which underpin economics are difficult to measure, we should simply avoid them. Rational choice theory, pioneered by Lionel Robbins, postulated that individuals perform a cost-benefit analysis to determine whether to pursue a particular course of action – a way of thinking that quickly came to dominate mainstream thinking. However, rational choice theory could never explain why individuals undertake actions that appeared not to yield any direct benefit to them, such as charitable giving. But by the time economists began to understand that a whole range of cultural factors determined why individuals took a particular course of action, so entrenched was the culture of positivism that it became increasingly difficult to challenge the status quo.

Whilst economics has gone to great lengths to sidestep the moral issues which its analysis throws up, as Timothy Taylor put it “moral judgments aren’t willing to sidestep economics.” As he points out, economics starts to get into difficulties when it becomes subject to “mission creep”. At the heart of the problem is the reliance on the price mechanism to assign value to a particular activity. But this quickly falls down when valuing an activity which is deemed ethically dubious or where the price mechanism is simply not the appropriate tool.

I have often thought that this reliance represents a form of economic singularity – the point at which conventional laws break down. Indeed, my own reservations stem back to my undergraduate days when I was taught that the cost benefit analysis of health programmes was based upon the value of human capital defined on the basis of lifetime earnings. This never struck me as sensible. I later came to realise that the relevant metric is willingness to pay to avoid particular outcomes – a cost that could potentially become infinite in order to avoid the worst-case outcomes. It is precisely because of such calculations that I have been rather scathing over the years about the field of health economics which takes a very narrow cost-benefit approach to one of the most fundamental issues we face – the matter of life and death itself (in fairness, it has moved in the direction of willingness to pay analysis in recent years, thus mitigating part of my criticism).

Why this matters

The issue of ethics in economics is an important one. Policy cannot be framed without some reference to what society deems morally acceptable. It is simply not enough to adopt a positivist approach. In macro terms we can debate the righteousness of the guiding principles followed by the Reagan and Thatcher governments of the 1980s but they were at least coherent: They were designed to reduce the role of state interference in the lives of ordinary citizens and empower the individual. In other words, there was a normative element to the policy. As it happens, they focused on a very narrow set of criteria which boosted short-term material prosperity but failed to take account of the wider long-term costs (rising inequality and the hollowing out of the industrial base to name but two). Nonetheless, the ideas were so electorally popular that subsequent generations of politicians on the other side of the political divide (Clinton/Obama and Blair/Brown) did not try to reverse the tide and instead tried to marry it with the idea of promoting social justice.

In recent years neither the US nor UK policy agenda appear to have been guided by any form of coherent economic thinking. Starting in 2010, the British government adopted a positivist approach based around deficit reduction but this had significant adverse consequences for the less well-off members of society and played a big role in whipping up the discontent which ultimately led to the Brexit vote. The populist governments which emerged post-2016, notably those led by Trump and Johnson, do not appear to offer any coherent economic vision at all.

Trump’s economic policy was based around an America first philosophy which served only to trash the global rules-based order and lit the touchpaper for the disaster which has unfolded in Afghanistan in recent days. Even leaving this catastrophe aside, pursuing what amounts to an isolationist stance in an increasingly interconnected world makes little sense as an economic strategy. The Johnson government has followed a similar stance in that it has trashed the UK’s relationships with its erstwhile European partners. But the criticism most frequently levelled at the Johnson government is that its policies are opportunistic rather than aimed at a coherent set of normative goals. There are some elements of a moral economic policy – notably the promise to “level up” regional inequalities – but over the last year its actions have created an impression that it is out to secure the interests of its members rather than the electorate it is meant to serve. Moreover, in areas such as NHS reform and defence spending – both of which are driven by economic considerations – there is no sense of a coherent, principled approach.

All this gives economics a bad rap, partly because politicians tend to blur the lines between complex economic issues and simple budgetary concerns. Economic policy should concern itself with the wider implications of its actions rather than focusing merely on the monetary aspects. Whether or not people think of economics as a science matters less than the fact that it has roots which emerge from its philosophical traditions, and we would do well to remember that sometimes we have to think in terms of more than assigning monetary values to policy objectives. Adam Smith would undoubtedly have approved.

A Nobel cause

Economics is a social science and although many economists do not like to admit it, it is bracketed alongside disciplines such as anthropology and psychology. Indeed, in the second half of the eighteenth century, when Adam Smith was setting out the principles of the invisible hand so beloved in market analysis, psychology did not exist as a separate discipline. The work of many of the early economists such as Smith and Jeremy Bentham, was closely intertwined with issues which are now the preserve of academic psychologists. Economics thus has deep roots in the field of psychology.

Despite the best efforts of the profession to move away from the imprecision of psychological concepts, many of the paradigms explaining economic behaviour failed to stand up to rigorous testing. Whilst these were initially explained away as anomalies which did not negate the underlying assumptions, developments in cognitive psychology from the 1960s began to be seen in some quarters as better explanations of certain forms of economic behaviour. Over the last 20-30 years, a number of these insights, derived from experimental psychology, have been applied to economic and financial decision making as better explanations of behaviour than the standard model. The new field of behavioural economics, for which Richard Thaler this week won the 2017 Nobel Prize for economics, examines what happens when we relax the assumptions of rationality and perfect information which underpin much of modern macroeconomics.

Amongst the range of judgement and decision biases which clearly violate the principle of rationality, behavioural economists have focused on factors such as overconfidence, wishful thinking, conservatism, belief perseverance, availability biases and anchoring (estimates based on an initial, often random, value). Using a combination of empirical evidence and thought experiments, academic researchers have demonstrated that some of these characteristics are at work in driving the expectations formation process. For example, evidence for the overconfidence hypothesis suggests that the confidence intervals assigned to outcomes tend to be too narrow. In a famous 1974 paper, Kahneman and Tversky[1] find evidence that whilst individuals often start off with an initial value in making estimates of future values, they are often reluctant to make big adjustments to this estimate when revising their assessment (the anchoring problem). This might go some way towards explaining why economists are reluctant to radically change their forecasts on a regular basis.

We could go on, but the point is made that there is enough empirical evidence to challenge the rational expectations assumption and thereby the idea that markets are efficient. This is a problem for many economists to deal with, for they have often spent years learning to deal with the sophisticated mathematics underpinning their stochastic models, which use rational expectations as a convenient simplifying assumption. It is an even bigger problem for the finance industry which spent many decades convincing itself that prices adequately reflect all available information.

One of the great ironies of a trading environment is that if rationality is common knowledge, there ought to be relatively little trading since a rational investor should be reluctant to buy if another investor is willing to sell. But the converse is true since the trading volume on world exchanges continues to rise. Indeed, much of the empirical evidence suggests that traders would make higher returns if they trade less frequently. Moreover, the same body of research indicates that investors are unwilling to sell assets which trade at a loss relative to the price at which they were purchased – behaviour which may well reflect an irrational belief in mean-reversion.

There are also clear patterns in purchasing decisions where there is evidence to suggest that investors buy stocks which have previously been big winners (in the hope that this performance will be repeated) or big losers (in the expectation of mean reverting performance). Neither of these is consistent with rational behaviour, but one reason why investors may follow such strategies is that they do not have time to systematically analyse the whole range of stocks. The choice of which to sell is limited to the range of stocks currently owned, but the range of stocks from which investors can choose to buy is enormous, and they are attracted to the outliers in what is known as the attention effect.

Clearly, markets display characteristics at odds with efficiency and expectations are not always formed rationally. The world thus owes a debt to Thaler and his colleagues for pointing out some of the absurdities in conventional economic thinking. Behavioural economic does not have all the answers. In the minds of many people it is just a collection of theories which can only ever be tested on small samples and thus its wider applicability is limited. But to the extent that it makes us think about some of the reasons why economics has not always come up with the right answers, Thaler’s award is well deserved.

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[1] Kahneman, D. and Tversky, A. (1974) 'Judgement Under Uncertainty: Heuristics and Biases,' Science, 185, 1124-1131

Getting our facts right

A few weeks ago I was involved in a debate with a young analyst who refused to believe that exchange rates are driven by factors other than trade deficits (not current accounts, simply the flow of trade in goods). After fruitless attempts to try and engage in some form of intellectual debate, only to be met each time with the stock response “I disagree,” I simply shut down the conversation. This is not my preferred mode of interaction – far from it. We learn from discourse and I like to think I am open to changing my mind on various issues if the facts prove I was wrong.

It was in this vein that I read with interest a blog piece by Noah Smith entitled “Is economics a science?” "Real" scientists would treat the question with contempt and indeed I never try to claim that it is. But what economics tries to do is measure and draw inference from observation. In that respect it employs scientific methods even if it does not always result in scientific conclusions. One reason why the theory and practice differ so much is that the logical economic answer is not always politically acceptable. Economics also has deep philosophical roots which colour the prior beliefs of many practitioners. Indeed, one of Adam Smith’s noted works - admired by many on the political right - was a Theory of Moral Sentiments published 17 years before the Wealth of Nations. It is perhaps these philosophical underpinnings which explain why adherents to the Austrian school of economic thought, which also derives from a branch of philosophy, eschew empiricism in favour of a priori deduction in order to reach a conclusion.

I could not help thinking during the Brexit debate last year that many of the leading Brexiteers were adherents of free market economics of the kind espoused by the Austrian school. It therefore does not surprise me that many of their arguments were not backed up by empirical analysis. I have also been struck by the apparent shift in tone of those who 12 months ago supported Brexit. Only today, the campaign director of Vote Leave, Dominic Cummings, admitted that “in some possible branches of the future leaving will be an error”  (let me correct you there, Dominic. In pretty much all branches of the future leaving will be an error). Cummings appears to be directing much of the blame for this on the way it has been handled by Downing Street. Personally, I prefer the explanation that those responsible for promoting the cause did not do their homework and failed to think through the implications of their actions.  In other words, they adopted a very unscientific approach.

However, we also have to be very careful when making arguments based on data alone. One of the issues which the academic world is currently very concerned about is the accuracy and replicability of much (non-economic) scientific work. Only last week, the president of the Royal Statistical Society, Professor Sir David Spiegelhalter, pointed out that public trust in scientific conclusions is being undermined by a “failure to adhere to good scientific practice and the desperation to publish or perish.” As Spiegelhalter points out, most scientists do not overtly falsify their data, but they sometimes play fast and loose with statistical inference (credit should also go to The Economist for having made this point repeatedly in recent years).

Aside from problems arising from the accuracy of results, economics suffers from another problem due to the quality of the underlying data. Although I do believe that economic statisticians are free from political bias, economic data often suffer from sample bias due to the fact that it is constructed by drawing population inferences from a relatively small sample. It is often an approximation to reality at best. A case in point is UK labour force data, where a tightening of the criteria for benefit eligibility means that many people whose fitness for work is questionable, have been reclassified as part of the labour force. UK immigration data are also not fit for purpose either, despite the fact that they form a key element in the government’s Brexit strategy (amongst other reasons, because the UK does not require migrants to register after arrival, the figures are compiled from the International Passenger Survey, which has numerous methodological shortcomings).

But for all that, a debate based on some form of data is always more informed than one based purely on belief and supposition. As the Canadian academic Marshall McLuhan pointed out, “a point of view can be a dangerous luxury when substituted for insight and understanding.” A year on from the Brexit referendum, that rings all the more true.